DESIGN AND EXPERIMENT OF A NEW ROTARY COATING MACHINE BASED ON LabVIEW

Zhang, Xiwen; Hou, Zhanjun; Dai, Nianzu

doi:10.35633/inmateh-65-10

Cited by 12 publications

(1 citation statement)

References 4 publications

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“…You Only Look Once (YOLO), with its unique architecture and modules, has demonstrated superior performance across numerous recognition tasks [27][28][29] . With the evolution of the YOLO series algorithms, YOLOv5 has gained increasing attention.…”

Section: Introductionmentioning

confidence: 99%

Recognition model for coated red clover seeds using YOLOv5s optimized with an attention module

Zhang,

Xuan,

Hou

2023

International Journal of Agricultural and Biological Engineering

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The non-destructive recognition of coated seeds is crucial for advancing studies in coating theory. Currently, the recognition of coated seeds heavily relies on manual visual inspection and machine vision detection. However, these methods pose challenges such as high misclassification rates, low recognition efficiency, and elevated labor intensity. In response to the aforementioned challenges, this study leveraged deep learning techniques to develop a coated seed recognition model named YOLO-Coated Seeds Recognition (YOLO-CSR), aiming to address the challenges posed by coated seed recognition tasks. The experiment of this study mainly includes the following steps: First, a seed coating machine was set up to coat red clover seeds, resulting in three types of coated red clover seeds. Subsequently, by collecting images of the three types of coated seeds, a coated seed image dataset was further constructed. Then, the YOLOv5s was built, incorporating the Convolutional Block Attention Module (CBAM) into the model's backbone to enhance its ability to learn features of coated seeds. Finally, the training results of YOLO-CSR were compared with those of other classical recognition models. The experimental results showed that YOLO-CSR achieved the best recognition performance on the self-built coated seed image dataset. The average precision (AP) for recognizing the three types of coated seeds reached 98.43%, 97.91%, and 97.26%, with a mean average

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Section: Introductionmentioning

confidence: 99%

Recognition model for coated red clover seeds using YOLOv5s optimized with an attention module

Zhang,

Xuan,

Hou

2023

International Journal of Agricultural and Biological Engineering

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Experimental Study on the Pelleting and Coating Performance of Red Clover Seeds

Xue,

Ma,

Hou

et al. 2024

Coatings

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This study aimed to optimize the pelleting and coating process for red clover seeds, addressing the issue of low pelleting success rates. Through theoretical analysis and experimental research, coating pan fill rate, powder supply quantity, and pelleting time were identified as key factors influencing the pelleting success rate. Single-factor experiments were conducted to investigate the effects of these parameters on the quality of red clover seed pelleting and coating. Based on these results, orthogonal trials were carried out, and response surface analysis was employed to reveal the influence patterns and interactions of each factor. The research results indicate that the factors affecting the pelleting success rate, ranked in order of importance, are coating pan fill rate, pelleting time, and powder supply quantity. Through mathematical model optimization, the optimal combination of process parameters was determined to be coating pan fill rate of 35.9%, powder supply quantity of 160.2 g, and pelleting time of 6.9 s. Under these conditions, a pelleting success rate of 94.3% was achieved in validation experiments. This study provides a theoretical foundation and practical guidance for optimizing the pelleting and coating process of red clover seeds, which is significant for improving seed coating quality and promoting red clover cultivation.

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Design and Experiment of Self-Propelled Highland Barley Harvesting and Binding Machine

ZHONG,

YIN,

LIU

et al. 2023

INMATEH

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In view of the complex agronomic technology of highland barley production and the lack of special machinery for harvesting and bundling highland barley, the harvesting of highland barley is basically done manually. There is a seriously reduced degree of mechanization of highland barley harvesting. Therefore, this paper designs a self-propelled highland barley harvesting and bundling machine, which realizes a single operation process to complete mechanized complex operations such as harvesting, bundling and laying highland barley. By designing the highland barley harvesting method and cutting platform, the height of the cutting platform can be adjusted stepless, and the highland barley bundle knotter is designed to realize the regulation and control of the baling diameter of the highland barley. According to the design of the rope feeding mechanism, the gathering mechanism and the baling mechanism, the main parameters of the baling device are determined. The stubble cutting height of the machine is 325 mm, the average diameter of the highland barley bundles is 195 mm, the average weight per bundle is 5.08 kg, bale formation rate is 97.8%, the qualification rate of the straw bundle reaches 95.6%, drop resistance rate is 92.6%, operating efficiency is 0.82 ha/h. The harvest baler runs in low speed 1 gear, the machine has high operation efficiency, high bundling rate of highland barley, good paving effect, reduced labor intensity, provides the mechanized efficiency of highland barley harvesting. Fuel consumption per hectare is 8.05 kg.hm-2, and the three shifts are without fault, to sum up, it can meet the requirements of highland barley harvesting and baling. The above research can provide a reference basis for the design of the highland barley harvesting baler.

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DESIGN AND EXPERIMENT OF A NEW ROTARY COATING MACHINE BASED ON LabVIEW

Cited by 12 publications

References 4 publications

Recognition model for coated red clover seeds using YOLOv5s optimized with an attention module

Recognition model for coated red clover seeds using YOLOv5s optimized with an attention module

Experimental Study on the Pelleting and Coating Performance of Red Clover Seeds

Design and Experiment of Self-Propelled Highland Barley Harvesting and Binding Machine

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